ECE 110/120 Honors Lab Section : Movement control circuit

Name	NetID	Section
Yiming Gong	yimingg8	ECE 120
Hongchuan Cheng	hc43	ECE 120
Sakhiyuvio Farsya Yunalfian	sfy2	ECE 120

Statement of Purpose

Our project is a movement-controlled circuit that can detect some specific hand gestures and output corresponding signals. We will use LED as the controlled device. The goal is to recognize four different hand gestures, each provides a signal to turn on, turn off, lighten and darken the LED. The objectives of this project include using computer software to detect hand gestures and sending signals to the Raspberry Pi board where the main circuit is connected.

This project has potential usage in the area of remote control for home electric appliances. Such application can provide significant convenience for people, especially the disabled, in their everyday life.

Background Research

For hand gesture detection, we will install Tensorflow and OpenCV on Raspberry Pi 4. OpenCV provides the library for hand and hand gesture detection. Raspberry Pi Camera Module is used to transfer the information into the server, and finally, the signal is sent to the circuit which is connected to the Raspberry Pi. The inspiration for this project is the potential usage of remote control and the significant convenience it can bring. We get the inspiration from a project last year in which they built a movement-controlled car. We discovered that we can implement this idea into something with more real-life significance, so we decide to create a movement-controlled circuit to control electric devices like LED light, which has wider usage in real-life situations.

Block Diagram / Flow Chart

System Overview

The input of the system will be the image imported from the camera which is used to capture the movement of hands. The image information will be processed by the OpenCV in Raspberry Pi. The signal is returned and sent to the circuits connected to the board. The output of this system is the LED light, with different hand gestures, the light will have four states which are turned on, turned off, lightened, and darkened.

Parts

Price

Quantity

Purpose

Raspberry Pi 4

$35

1

This is the platform we will use to install OpenCV and Tensorflow, it is also connected to the main circuit to control it.

https://www.raspberrypi.com/products/raspberry-pi-4-model-b/

Raspberry Pi Camera Module

$25

1

This module is used to capture the hand movements and transfer the information to the server to process.

https://www.canakit.com/raspberry-pi-camera-v2-8mp.html?cid=usd&src=raspberrypi

Possible Challenges

This project requires the use of Tensorflow and Raspberry Pi, which we do not have experience with. We have to learn every detail from scratch, maybe even how to install them properly.

References

Renotte, N., 2022. Sign Language Detection using ACTION RECOGNITION with Python | LSTM Deep Learning Model. [online] Youtube.com. Available at: <https://www.youtube.com/watch?v=doDUihpj6ro&t=1476s> [Accessed 20 February 2022].

Choudhary, A., 2022. Hand Gesture Recognition using Raspberry Pi and OpenCV. [online] Circuit Digest. Available at: <https://circuitdigest.com/microcontroller-projects/hand-gesture-recognition-using-raspberry-pi-and-opencv> [Accessed 20 February 2022].

Youtube.com. 2022. How to install OpenCV on Raspberry Pi 4 | Raspberry Pi Tutorials for Beginners (2020). [online] Available at: <https://www.youtube.com/watch?v=ylnjXbcNLJU> [Accessed 20 February 2022].